9 citations · 29 across the 16 of their papers we have counts for
17 papers
Lost in the Fallback: How Reliably Do Typed Decision Models Use Fallback Options?
Yuanbo Xie, Mingli Zhu, Tianyun Liu +3
Typed decision models (TDMs) are increasingly used in applications such as request routing and model selection, making reliable decisions critical to system performance. Fallback o…
Towards Human-Like Manipulation through RL-Augmented Teleoperation and Mixture-of-Dexterous-Experts VLA
Tutian Tang, Xingyu Ji, Wanli Xing +7
While Vision-Language-Action (VLA) models have demonstrated remarkable success in robotic manipulation, their application has largely been confined to low-degree-of-freedom end-eff…
Stereo-Inertial Poser: Towards Metric-Accurate Shape-Aware Motion Capture Using Sparse IMUs and a Single Stereo Camera
Tutian Tang, Xingyu Ji, Yutong Li +3
Recent advancements in visual-inertial motion capture systems have demonstrated the potential of combining monocular cameras with sparse inertial measurement units (IMUs) as cost-e…
FSGlove: An Inertial-Based Hand Tracking System with Shape-Aware Calibration
Yutong Li, Jieyi Zhang, Wenqiang Xu +2
Accurate hand motion capture (MoCap) is vital for applications in robotics, virtual reality, and biomechanics, yet existing systems face limitations in capturing high-degree-of-fre…
FBI: Learning Dexterous In-hand Manipulation with Dynamic Visuotactile Shortcut Policy
Yijin Chen, Wenqiang Xu, Zhenjun Yu +4
Dexterous in-hand manipulation is a long-standing challenge in robotics due to complex contact dynamics and partial observability. While humans synergize vision and touch for such…
DexTOG: Learning Task-Oriented Dexterous Grasp with Language
Jieyi Zhang, Wenqiang Xu, Zhenjun Yu +3
This study introduces a novel language-guided diffusion-based learning framework, DexTOG, aimed at advancing the field of task-oriented grasping (TOG) with dexterous hands. Unlike…
DiPGrasp: Parallel Local Searching for Efficient Differentiable Grasp Planning
Wenqiang Xu, Jieyi Zhang, Tutian Tang +3
Grasp planning is an important task for robotic manipulation. Though it is a richly studied area, a standalone, fast, and differentiable grasp planner that can work with robot grip…
Kalib: Easy Hand-Eye Calibration with Reference Point Tracking
Tutian Tang, Minghao Liu, Wenqiang Xu +1
Hand-eye calibration aims to estimate the transformation between a camera and a robot. Traditional methods rely on fiducial markers, which require considerable manual effort and pr…
MS-MANO: Enabling Hand Pose Tracking with Biomechanical Constraints
Pengfei Xie, Wenqiang Xu, Tutian Tang +2
This work proposes a novel learning framework for visual hand dynamics analysis that takes into account the physiological aspects of hand motion. The existing models, which are sim…
Precise Robotic Needle-Threading with Tactile Perception and Reinforcement Learning
Zhenjun Yu, Wenqiang Xu, Siqiong Yao +5
This work presents a novel tactile perception-based method, named T-NT, for performing the needle-threading task, an application of deformable linear object (DLO) manipulation. Thi…
RFTrans: Leveraging Refractive Flow of Transparent Objects for Surface Normal Estimation and Manipulation
Tutian Tang, Jiyu Liu, Jieyi Zhang +3
Transparent objects are widely used in our daily lives, making it important to teach robots to interact with them. However, it's not easy because the reflective and refractive effe…
GarmentTracking: Category-Level Garment Pose Tracking
Han Xue, Wenqiang Xu, Jieyi Zhang +5
Garments are important to humans. A visual system that can estimate and track the complete garment pose can be useful for many downstream tasks and real-world applications. In this…
Level 2 Autonomous Driving on a Single Device: Diving into the Devils of Openpilot
Li Chen, Tutian Tang, Zhitian Cai +6
Equipped with a wide span of sensors, predominant autonomous driving solutions are becoming more modular-oriented for safe system design. Though these sensors have laid a solid fou…
RFUniverse: A Multiphysics Simulation Platform for Embodied AI
Haoyuan Fu, Wenqiang Xu, Ruolin Ye +7
Multiphysics phenomena, the coupling effects involving different aspects of physics laws, are pervasive in the real world and can often be encountered when performing everyday hous…
ContourRender: Detecting Arbitrary Contour Shape For Instance Segmentation In One Pass
Tutian Tang, Wenqiang Xu, Ruolin Ye +2
Direct contour regression for instance segmentation is a challenging task. Previous works usually achieve it by learning to progressively refine the contour prediction or adopting…
H2O: A Benchmark for Visual Human-human Object Handover Analysis
Ruolin Ye, Wenqiang Xu, Zhendong Xue +3
Object handover is a common human collaboration behavior that attracts attention from researchers in Robotics and Cognitive Science. Though visual perception plays an important rol…
Learning Universal Shape Dictionary for Realtime Instance Segmentation
Tutian Tang, Wenqiang Xu, Ruolin Ye +2
We present a novel explicit shape representation for instance segmentation. Based on how to model the object shape, current instance segmentation systems can be divided into two ca…